1. Field of the Invention
The disclosure is directed to dynamic power management of context aware services.
2. Description of the Related Art
Wireless communication systems have developed through various generations, including a first-generation analog wireless phone service (1G), a second-generation (2G) digital wireless phone service (including interim 2.5G and 2.75G networks) and third-generation (3G) and fourth-generation (4G) high speed data/Internet-capable wireless services. There are presently many different types of wireless communication systems in use, including Cellular and Personal Communications Service (PCS) systems. Examples of known cellular systems include the cellular Analog Advanced Mobile Phone System (AMPS), and digital cellular systems based on Code Division Multiple Access (CDMA), Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), the Global System for Mobile access (GSM) variation of TDMA, and newer hybrid digital communication systems using both TDMA and CDMA technologies.
More recently, Long Term Evolution (LTE) has been developed as a wireless communications protocol for wireless communication of high-speed data for mobile phones and other data terminals. LTE is based on GSM, and includes contributions from various GSM-related protocols such as Enhanced Data rates for GSM Evolution (EDGE), and Universal Mobile Telecommunications System (UMTS) protocols such as High-Speed Packet Access (HSPA).
Certain types of user equipments (UEs), such as smart phones, tablet computers, and the like, are built on a mobile operating system and can download and install third-party applications (a.k.a. “apps”). These UEs have a number of hardware subsystems that can be accessed by installed applications to provide features and functionality to a user.
Multiple applications, residing above the operating system level, may wish to simultaneously leverage multiple context awareness services, residing below the operating system level. This can impact power consumption. Examples of such services include geo-fencing, place clustering, audio environment clustering, target sound detection (e.g. speech, typing), motion state and device position classification, proximity discovery, target situation detection (e.g. driving, in meeting, alone, sleeping, etc.), and the like.
In many cases, the performance of a context awareness service degrades gradually when the power allocated to it is reduced. For example, the performance of a speech detector or an audio clustering algorithm operating on duty-cycled audio data degrades gracefully when the duty-cycle is reduced. This suggests that rather than allowing power consumption to increase with each new service, or arbitrarily killing services, the power allocated should simply be adjusted to satisfy the constraints of a power budget.